PyMCT and PyCPL: Refactoring the Community Climate System Model

Coupled climate models are multiphysics models comprising multiple separately developed codes that are combined into a single physical system. This composition of codes is amenable to a scripting solution, and Python is a language that offers many desirable properties for this task. We have prototyped a version of the Community Climate System Model (CCSM) with coupling infrastructure written in Python. Our objective was to improve dramatically CCSM’s already flexible coupling infrastructure to enable research uses of the model not currently supported. Here we report the progress in the first steps in this effort: the construction of Python bindings for the Model Coupling Toolkit, a key piece of third-party coupling middleware used in CCSM, and a Python-based CCSM coupler application. We find that the choice of Python over the original Fortran implementation in the coupler imposes minimal visible performance impact to the overall coupled system. We believe our results augur well for the use of Python in the top-level coupling and organisation of large parallel multiphysics and multiscale applications. Dept. of Geophysical Sciences, University of Chicago, Chicago, IL, USA. mailto: [email protected] Mathematics & Computer Science Division, Argonne National Laboratory, Argonne, Illinois, USA Computation Institute, University of Chicago, Chicago, IL, USA ANU Supercomputer Facility, The Australian National University, Canberra, Australia Australian Partnership for Advanced Computing (APAC) Dept. of Atmospheric and Oceanic Sciences, University of Wisconsin, Madison, WI,